Potential of bat pass duration measures for studies of bat activity

<p>Acoustic detectors have become increasingly used by bat workers to investigate bat ecology and assess the impacts of anthropogenic pressures. Within these studies, the metric used, ‘bat activity’, is based on the number of bat passes, without considering the bat pass duration (i.e. each event of a bat detected within the range of an ultrasonic detector). We expected that bat pass duration may contain information about site quality in terms of foraging potential. Because bats are expected to have a more sinuous trajectory and slower velocity when they exhibit foraging behaviour, as opposed to commuting behaviour, we hypothesize a longer bat pass duration in favourable habitats; during seasons with important energetic demands; or during night peak activity. We used datasets from a large-scale acoustic bat survey (<i>n</i> = 2890 sites), with a total of 24,597 bat pass measures from 6 taxa, and performed GLMM modelling. We detected a significant effect of habitat type on bat pass duration for five taxa. Shorter bat pass durations were detected at the beginning of the night. We detected longer pass durations during the lactation period or just before hibernating, while weather conditions or ageing and wear of the detector rarely influenced bat pass duration. Bat pass duration appears to be a simple and easy measure for position calls on a gradient between commuting vs. foraging behaviour. We suggest that the traditional measure of bat activity may be weighted by bat pass duration by giving more weight to events with potentially stronger links to foraging behaviour.</p

Definition of the ecological niche used in this article.

<p>(<b>A</b>) The environmental space can be represented as a set of axes (here, two: <i>X</i>, <i>Y</i>), each representing a gradient of resource or condition. A species' niche is defined as the range of each of these gradients that the species can exploit/occupy/cope with (yellow ellipse). The projection of the niche on each gradient is defined by a position (<i>P_x</i>, <i>P_y</i>) and a breadth (red solid lines). In our analyses, we consider two axes: (<b>B</b>) <b>a thermal axis</b> (referred to in the text as ‘thermal niche’) corresponds to a gradient of temperature; (<b>C</b>) <b>a habitat axis</b> (‘habitat niche’) refers to a gradient of vegetation structure ranging from mature forest to grasslands and open fields (see also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032819#pone-0032819-t001" target="_blank">Table 1</a>).</p

Relationship between thermal and habitat niches for 74 European bird species.

<p>(<b>A</b>) Relationship between niche positions; (<b>B</b>) relationship between niche breadths. The linear relationships (dashed lines) and their confidence intervals (dotted lines) are derived from averaged coefficients resulting from phylogenetic generalized least square regressions, after AICc-based model selection. Thermal positions and breadths are log transformed to approach a normal distribution. Both thermal and habitat positions are scaled to mean = 0, SD = 1. DELURB: <i>Delichon urbicum</i>, HIRRUS: <i>Hirundo rustica</i>. MOTALB: <i>Motacilla alba</i>. MOTFLA: <i>Motacilla flava</i>, PASDOM: <i>Passer domesticus</i>. PICPIC: <i>Pica pica</i>. STRDEC: <i>Streptopelia decaocto</i>. STRTUR: <i>Streptopelia turtur</i>.</p

Results of the model selection process.

<p>Models are phylogenetic generalized least square regressions with either climatic niche position or breadth as the response variable. Fixed predictors included migratory status (migr), age of first breeding (AFB), and either habitat niche position (HPI) or breadth (SSI) according to the model. The intercept is noted <i>γ</i>; <i>k</i> corresponds to the number of model parameters. The ΔAICc refers to the difference between the AICc of model <i>i</i> and that of the model with the lowest AICc value. The column “weight” refers to AICc weights, which were used to compute the averaged coefficients of the fixed effects.</p